No-till corn performance in response to P and fertilization modes

No-tillage systems provide soil changes that affect nutrient dynamics, hence, changing rates and forms of fertilizer application. This study aimed to evaluate the effect of phosphorus (P) and modes of nitrogen (N) and P application in corn under long-term no-tillage in a clayey Oxisol. Two experiments were carried out in the same experimental area and in the same year, in a randomized blocks design with four replications. In experiment I, the treatments consisted of five doses of phosphorus (0, 40, 80, 120 and 160 kg ha-1 of P2O5) applied in the sowing furrow. In experiment II, the treatments consisted of the N and P application modes (topdressing, in the sowing furrow and control - without N and P). Experiment I evaluated the root length, P uptake and grain yield and, the Experiment II, the firing height and yield. The P rates provided linear increases in root length in the 0-10 cm layer, P uptake and grain production. The different modes of application provided differences in the firing height and corn yield. The control treatment (0 kg ha-1 of N and P) provided the highest firing height, superior than those of topdressing and application in the furrow, which were not significantly different. The topdress application of N and P provided an increase in corn yield that exceeded 16 and 42% of the application in the furrow and the control, respectively. Thus, the results confirmed that increasing rates of P2O5, in soil with high initial P content, influence positively corn production factors, but with little significant responses, and the topdress application of N and P on soil with high P content, without water restriction, provided increased grain yield in relation to the application in the furrow.

Efficiency and response of conilon coffee clones to phosphorus fertilization

Studies on nutritional efficiency of phosphorus in conilon coffee plants are important tools to unravel the high limitation that natural low levels of this nutrient in soil impose to these species cultivars. Therefore, this study aimed at evaluating the nutritional efficiency and the response to phosphorus of conilon coffee clones. Plants were managed during 150 days in pots containing 10 dm³ of soil, in greenhouse. A factorial scheme 13 x 2 was used, with three replications, being the factors: 13 clones constituting the clonal cultivar "Vitória Incaper 8142" and two levels of phosphate fertilization (0% and 150% of the P2O5 usualy recommended), in a completely randomized design (CRD). The results indicate a differentiated response of dry matter production and of phosphorus content on each level of phosphate fertilization for the conilon coffee clones and that CV-04, CV-05 and CV-08 clones are nutritionally efficient and responsive to the phosphate fertilization.

Nitrogen fertilization of coffee: organic compost and Crotalaria juncea L.

Information concerning the response of coffee to organic fertilizers is scarce. This study evaluates the effect of different doses of compost and Crotalaria juncea L. on growth, production and nitrogen nutrition of coffee trees. The treatments consisted of compost at rates of 25, 50, 75 and 100% of the recommended fertilization, with or without the aerial part of C. juncea. C. juncea was grown with NH4-N (2% 15N) and applied to coffee. The use of C. juncea increased growth in height and diameter of the coffee canopy. In the first year, the percentage of N derived from C. juncea reached 8.5% at seven months and 4.1% at fifteen months after fertilization. In the second year, the percentage of N derived from C. juncea reached 17.9% N at the early harvest, five months after fertilization. Increased rates of compost increased pH , P , K , Ca , Mg , sum of bases , effective CEC, base saturation and organic matter and reduced potential acidity. 15N allowed the identification of the N contribution from C. juncea with percentage of leaf N derived from Crotalaria juncea from 9.2 to 17.9%.

Maize nitrogen fertilization in two crop rotation systems under no-till

The objective of this study was to evaluate split nitrogen (N) fertilization of maize applied in band at sowing and top dressing with and without crop rotation, under no-till. The experiment was conducted with six N rates at sowing (0, 20, 30, 40, 50 and 60 kg ha-1) combined with three rates in top dressing (40, 70, 100 kg ha-1) and two management systems: after five cropping sequences of maize and crop rotation (maize + soybean + oat + soybean + corn) in a randomized block design with four replications. The crop rotation system increased yield in approximately 7% in relation to the area without rotation. The split of nitrogen fertilization, in rates above 39 and 54 kg ha-1 at sowing and 70 and 40 kg ha-1 in top dressing, resulted in yield higher than that obtained with the application of 100 kg ha-1 in top dressing. Grain yield was higher with the rates 50 and 70 kg ha-1 of N compared with that obtained with 20 and 100 kg ha-1 at sowing and top dressing, respectively. The rate 70 kg ha-1 of N resulted in the highest yield at the lowest cost compared with the revenues and costs incurred with the rates 40 and 100 kg ha-1.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Spacing, population density and nitrogen fertilization in corn grown in an Oxisoil

The objective of this study was to evaluate yield components, leaf nitrogen content and grain yield in corn as affected by row spacing, plant density and nitrogen topdressing. The experiment was conducted with the single-cross hybrid AG 8021, in the municipality of Toledo-PR, in an Oxisoil under no-tillage system, in the crop year 2005/ 2006. The experiment was arranged in a randomized block design and treatments in split-split-plots, with four replications. The two row spacings (0.45 and 0.90 m) were allocated in the main plots, the two plant densities (60,000 and 80,000 plants ha-1) were allocated in the subplots and the three nitrogen rates (80, 100, 120 and 140 kg ha-1 N) were allocated in the sub-subplots. Topdress nitrogen was applied using urea as N source. The rise of the plant population from 60,000 to 80,000 plants ha-1 and the application of topdress nitrogen resulted in increased production components. The application of topdress fertilization provided increase in leaf N content and grain yield for the spacings 0.45 m and 0.90 m. Yield was higher in the spacing 0.45 m than 0.90 m. Yield was higher with 60,000 plants than with 80,000 plants at 0.90 m, while at 0.45 m there was no difference in relation to the plant density.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Growth and yield of corn hybrids in response to association with Azospirillum brasilense and nitrogen fertilization

There is a growing interest in optimizing the positive effects of the association between Azospirillum bacteria and corn crop in order to reduce the use of nitrogen fertilizers. This study aimed to evaluate the inoculation efficiency of an A. brasilense-based commercial product in association with different rates of nitrogen fertilization in two corn genotypes. The experiment was arranged in a 2 x 2 x 5 factorial randomized block design, with four replications. The treatments consisted of two corn hybrids (30F53 and CD386); with and without inoculation with a commercial product based on A. brasilense and five nitrogen rates (0, 40, 80, 120 and 160 kg ha-1). The variables plant height, basal stem diameter, leaf area, shoot dry matter, leaf nitrogen content, length and diameter of the cob, weight of 100 grains and grain yield were evaluated. Inoculation with A. brasilense provided increases of 11 and 12% in leaf area and shoot dry matter, respectively. There were differences in the response of the corn hybrids for most variables and the increase in nitrogen supply provided increments in the growth and yield of corn.

Nitrogen and potassium fertilization on the yield and intensity of the maize white spot

A plant's nutritional balance can influence its resistance to diseases. In order to evaluate the effect of increasing doses of N and K on the yield and severity of the mayze white spot, two experiments were installed in the field, one in the city of Ijaci, Minas Gerais, and the other in the city of Sete Lagoas, Minas Gerais. The experimental delimitation was in randomized blocks with 5 x 5 factorial analysis of variance, and four repetitions. The treatments consisted of five doses of N (20; 40; 80; 150; 190 Kg ha-1of N in the experiments 1 and 2) and five doses of K (15; 30; 60; 120; 180 Kg ha-1of K in experiment 1 and 8.75; 17.5; 35; 50; 100 Kg ha-1of K in experiment 2). The susceptible cultivar 30P70 was planted in both experiments. The plot consisted of four rows 5 meters long, with a useful area consisting of two central rows 3 meters each. Evaluations began 43 days after emergence (DAE) in the first experiment and 56 DAE in the second one. There was no significant interaction between doses of N and K and the disease progress P+. The effect was only observed for N. The K did not influence the yield and the severity of the disease in these experiments. Bigger areas below the severity progress curve of the white spot and better yield were observed with increasing doses of N. Thus, with increasing doses of N, the white spot increased and also did the yield.

Influence of foliar fertilization with manganese on germination, vigor and storage time of RR soybean seeds

ABSTRACTThis study aimed to evaluate the influence of foliar fertilizer doses containing Mn of phenological stages of suggested application in RR soybeans, to recover management damages with glyphosate at postemergence application on seed vigor in post-harvest and post six months storage. The seeds originated from a field experiment conducted , which included two applications of glyphosate, concomitant with foliar fertilizer in growth stages V4 and V6, with 0.00, 113.50 and 227.00 mg ha-1doses of Mn2+. Germination, GSI (Germination Speed Index), electrical conductivity tests and the first count of seeds were conducted. The application of Mn did not affect the physiological quality of RR soy in postharvest. However, in post-storage, higher doses of Mn had a negative effect on tests of abnormal seedlings, GSI and electrical conductivity. The applications of Mn, regardless of the developmental stage, did not interfere in the germination and first count tests, with and without storage. The electrical conductivity test showed a higher correlation with the seed germination test in the post-harvest treatment.

Effects of growth reducer and nitrogen fertilization on morphological variables, SPAD index, interception of radiation and productivity of wheat

ABSTRACT The objective of this study was to evaluate the effect of growth reducer and nitrogen fertilization on morphological variables, SPAD index, radiation interception, and grain yield of three cultivars of wheat. The experimental design was a randomized block in factorial scheme 3x5x2, with three cultivars (Mestre, Iguaçú and Itaipú), five nitrogen doses (0, 40, 80, 120, 160 Kg ha-1), and application or no application of a growth reducer, with three replications. The following characteristics were evaluated: plant height, SPAD index, leaf area index (LAI), Global Radiation Interception (GRI) and grain yield. The Tukey test (p < 0.05) was used for the comparison between the means of cultivar and growth reducer factors, and for a regression analysis to evaluate N levels. Increasing the dose of nitrogen promotes an increase in LAI of plants of wheat crops differently among cultivars, which leads to a greater degree of global radiation interception. At doses higher or equal to 120 Kg ha-1 of nitrogen, there are significant differences in grain yield between treatments with and without the application of the growth reducer. The significant interaction between growth reducer and nitrogen dose, showed that applications of growth reducer increase the GRI at doses above and below 80 Kg ha-1 of nitrogen. Nitrogen rates of 138 and 109 Kg ha-1 are responsible for maximum grain yields of wheat, which is 4235 and 3787 Kg ha-1 with and without the use of growth reducer, respectively.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Carbohydrates Concentration in leaves of potato plants affected by nitrogen fertilization rates

ABSTRACT At poor conditions of nitrogen (N) in the soil, potato plants may accumulate starch in leaves and be indicative of N nutritional stress. The objective of this work was to determine the effects of N rates (0, 50, 100, 200 and 300 kg ha-1 of N) on the concentrations of carbohydrates (total soluble sugars-TSS, reducing sugars-RS, non-reducing sugars-NRS and starch) in the fourth leaf (FL) of two potato cultivars (Asterix and Atlantic) and their critical levels (CL) associated to the N fertilization rate necessary to obtain the maximum physical (MPE) and economic (MEE) efficiency of tubers. A randomized block design with four replications was used in both experiments. On day 21 after plant emergence, four FL were collected from four plants. Potatoes plants fertilized with low rates of N accumulated less TSS in leaves than those properly fertilized. The opposite occurred with content of starch. The cultivars showed similar responses to five doses of N in relation to contents of starch and TSS. However, the response to the increase in doses of N for RS, NRS and Starch/NRS is cultivar-specific. The correlations between contents of RS, NRS and Starch/NRS with the starch and TSS were dependent on the potato cultivar.